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Increased equivalent conicity of wheels because of hollow wear during long-term operation influences the ride comfort performance of Chinese high-speed trains. To investigate the evolution of wheel wear, a high-speed train operating on the Beijing-Shanghai Railway line at maximum operational speed of 350 km/h is monitored over a time of 1.5 years. An MBS based wear calculation software tool of KTH using stochastic simulation inputs has been used for wear prediction, where the vehicle suspension parameters and global structural modes of car-body and bogie frame have been identified using roller rig measurements and dynamic track measurements as well to validate the simulation models. The calculated wear is then validated against measurements by calibrating the wear rate coefficients. The influence of initial conicity on the lateral wear distribution is analyzed. Wheel profiles with lower initial conicities result in significantly less wear but more vibrations which possibly worsen the ride comfort. Increasing the roll-stiffness shows to be an effective way to damp the low frequency vibrations for the low conicity wheel while resulting in low wear. The suspension parameters and initial conicity which give the most stable equivalent conicity evolution and best ride comfort are selected for field tests.

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Prediction and Control of Wheel Wear of a High-Speed Train Based on Measured Data and Simulation

  • 会议论文

  • 发表日期：

    2025年

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  • Xin Ding,
  • Elham Khoramzad,
  • Rocco Giossi,
  • Saeed Hossein Nia,
  • Helmut Netter,
  • Gang Chen,
  • Zhendong Liu,
  • Sebastian Stichel

摘要

Increased equivalent conicity of wheels because of hollow wear during long-term operation influences the ride comfort performance of Chinese high-speed trains. To investigate the evolution of wheel wear, a high-speed train operating on the Beijing-Shanghai Railway line at maximum operational speed of 350 km/h is monitored over a time of 1.5 years. An MBS based wear calculation software tool of KTH using stochastic simulation inputs has been used for wear prediction, where the vehicle suspension parameters and global structural modes of car-body and bogie frame have been identified using roller rig measurements and dynamic track measurements as well to validate the simulation models. The calculated wear is then validated against measurements by calibrating the wear rate coefficients. The influence of initial conicity on the lateral wear distribution is analyzed. Wheel profiles with lower initial conicities result in significantly less wear but more vibrations which possibly worsen the ride comfort. Increasing the roll-stiffness shows to be an effective way to damp the low frequency vibrations for the low conicity wheel while resulting in low wear. The suspension parameters and initial conicity which give the most stable equivalent conicity evolution and best ride comfort are selected for field tests.